Decorrelation Methods of Texture Feature Extraction
Abstract
This paper presents the development and evaluation of a visual texture feature extraction method based on a stochastic field model of texture. Results of recent visual texture discrimination experiments are reviewed in order to establish necessary and sufficient conditions for texture features that are in agreement with human discrimination. A texture feature extraction technique involving autocorrelation function measurement of a texture field, combined with histogram representation of a statistically decorrelated version of the texture field, is introduced. The texture feature extraction method is evaluated in terms of a Bhattacharyya distance measure.
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- Authors
- Faugeras, O. D., & Pratt, W. K.
- Affiliations
- University of Southern California (US)
- ORCID
- Faugeras, Olivier D.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1980-07
- Volume
- PAMI-2
- Issue
- 4
- Pages
- 323-332
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2012374219
- Cited by
- 138
- References
- 19
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 2 · 2022: 1 · 2021: 1 · 2020: 2 · 2019: 2 · 2018: 2 · 2016: 2 · 2015: 1 · 2014: 2
- FWCI
- 7.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Pattern Analysis and Machine Intelligence (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Keywords
- texture feature extraction, autocorrelation function, decorrelation, histogram representation, Bhattacharyya distance
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